Who this book is for

This book is for you if you are working with data. To get the most out of the book, you should have some familiarity with Python, particularly the pandas and numpy packages. In addition, some familiarity with data analytics is assumed, though the network science tools and problems we tackle are built from scratch for readers without a background in those problems or methods.

Network science has a rich history in many scientific disciplines, including epidemiology, biomedical engineering, sociology, genetics, environmental science, particle physics, computer science, and economics. Its foundations in graph theory influence research in many areas of pure and applied mathematics as well. Anyone in the fields of science, technology, engineering, and mathematics can benefit from network science’s toolset and approach to problem-solving.